ABSTRACT Uveal melanoma (UM) is the most common primary malignancy of the eye. The overall mortality rate is high (40%) because this aggressive cancer often metastasizes before ophthalmic diagnosis. Several gene mutations and chromosomal abnormalities have been associated with primary UM (pUM) development and metastasis, however the pathobiology of UM and mechanisms of metastasis remain poorly understood. Cytogenetic and molecular genetic analyses to detect pUM metastatic risk all require samples of tumor tissue. Survival rates have not improved for decades because pUM may metastasize prior to diagnosis and micrometastases may lie dormant for years. If available, blood-borne biomarkers with discriminatory accuracy for UM micrometastases would greatly improve prognostic methods, allow earlier detection of metastatic UM and enhance clinical patient care and survival. The long-term goals of this research are to better understand UM pathobiology, molecular mechanisms of UM metastasis, and to facilitate the development of blood-borne biomarkers. Using a cohort of 15 ocular pUM specimens, we have obtained quantitative proof-of-principal that proteomic differences exist between pUM that give rise to metastasis and those that do not. Our preliminary results have provided bioinformatic clues to mechanisms of UM metastasis and suggest candidate biomarkers from correctly classifying the metastasis risk in an independent test. We hypothesize that by expanding proteomic analyses to a cohort of 100 metastatic and non-metastatic pUM, we will establish with statistical rigor the identity of 20-30 differentially expressed proteins, and with bioinformatics, contribute new insights to UM mechanisms and pathobiology. We further hypothesize that differentially expressed proteins exhibiting discriminatory accuracy for metastatic status among an expended set of independent pUM tumor specimens will significantly enhance worldwide efforts to develop effective blood-borne biomarkers for UM metastasis. We now propose to combine extensive basic and clinical research experience; outstanding research environments; and strong preliminary data to address the molecular mechanisms of UM metastasis with the following two specific aims. (1) Expand iTRAQ LC MS/MS quantitative proteomic characterization to 50 metastatic and 50 non-metastatic primary UM to identify differentially expressed proteins. (2) Identify primary UM tumor proteins exhibiting high discriminatory accuracy for metastatic risk in an independent set of ? 45 ocular tumors. This research will validate for the first time quantitative proteomic differences between metastatic and non-metastatic pUM and bioinformatically advance understanding of UM pathobiology. A better molecular understanding of UM metastatic mechanisms will lead in the future to improved UM therapeutics, effective blood-borne biomarkers and UM patient management.